Computational protocol: Multi-platform metabolomics analyses of a broad collection of fragrant and non-fragrant rice varieties reveals the high complexity of grain quality characteristics

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Protocol publication

[…] Headspace volatiles were collected by solid phase micro-extraction (SPME) using a 65 µm polydimethylsiloxane-divinylbenzene fibre (Supelco, Bellefonte, USA) as described previously (Verhoeven et al. ). The volatile compounds were thermally desorbed at 250° C by inserting the fibre for 1 min into the GC injection port (GC 8000, Fisons Instruments, Cheshire, UK). The released compounds were transferred onto the analytical column (HP-5, 30 m × 0.25 mm ID, 1.05 μm film thickness) in splitless mode. The temperature program ran from 45 °C (2-min hold) and rose 5 °C min−1 to 250 °C (5-min hold). The column eluent was ionised by electron impact ionisation at 70 eV (MD800 electron impact MS, Fisons Instruments, Cheshire, UK). Mass scanning was done from 35 to 400 m/z with a scan time of 2.8 scans s−1. GC–MS raw data were processed using MetAlign software (Lommen ) to extract and align the mass signals (s/n ≥ 3). Mass signals below an s/n of 3 were randomized and given a value between 2.4 and 3 times the calculated noise value. Mass signals present in ≤6 samples were discarded. Signal redundancy per metabolite was removed by means of clustering and mass spectra were reconstructed using MSClust (Tikunov et al. ). Metabolites were identified by matching the mass spectra of detected metabolites to authentic reference standards and the NIST08, Wiley, and Wageningen Natural Compounds spectral library and by comparison with retention indices in the literature (Strehmel et al. ). […]

Pipeline specifications

Software tools MetAlign, MSClust
Application MS-based untargeted metabolomics
Organisms Oryza sativa